
where \(\mathbf {e} = \mathbf {x} - (\mathbf {y}_{:, 1} + \mathbf {y}_{:, 2})\) , and \(\zeta \in [0, 1]\)  is a tunable hyperparameter. The negative thresholded SNR [1]} is used as the loss:
\(\mathcal {L}^{\mbox{\tiny {SE}}} &= \alpha \mathcal {L}^{\mbox{\tiny {SNR}}}_{s, y_{:,1}} + (1-\alpha ) \mathcal {L}^{\mbox{\tiny {SNR}}}_{n, y_{:,2}},\\\mathcal {L}^{\mbox{\tiny {SNR}}}_{a,b} &= -10 \log _{10}(\Vert \mathbf {a}\Vert ^2 / (\Vert \mathbf {a} - \mathbf {b}\Vert ^2 + \tau \Vert \mathbf {a}\Vert ^2)),\) 
